LlamaIndex Postprocessor Integration: DashScope-Rerank
The llama-index-postprocessor-dashscope-rerank package contains LlamaIndex integrations for the gte-rerank series models provided by Alibaba Tongyi Laboratory.
Installation
pip install --upgrade llama-index llama-index-core llama-index-postprocessor-dashscope-rerank
Setup
Get started:
- Obtain the API-KEY from the Alibaba Cloud ModelStudio platform.
- Set API-KEY
export DASHSCOPE_API_KEY=YOUR_DASHSCOPE_API_KEY
Example:
from llama_index.core.data_structs import Node
from llama_index.core.schema import NodeWithScore
from llama_index.postprocessor.dashscope_rerank import DashScopeRerank
nodes = [
NodeWithScore(node=Node(text="text1"), score=0.7),
NodeWithScore(node=Node(text="text2"), score=0.8),
]
dashscope_rerank = DashScopeRerank(top_n=5)
results = dashscope_rerank.postprocess_nodes(nodes, query_str="<user query>")
for res in results:
print("Text: ", res.node.get_content(), "Score: ", res.score)
output
Text: text1 Score: 0.25589250620997755
Text: text2 Score: 0.18071043165292258
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| model | str |
model name | gte-rerank |
| top_n | int |
The number of top documents to be returned in the ranking; if not specified, all candidate documents will be returned. If the specified top_n value exceeds the number of input candidate documents, all documents will be returned. | 3 |
| return_documents | bool |
Whether to return the original text for each document in the returned sorted result list, with the default value being False. | False |
| api_key | str |
The DashScope api key. | None |
1 maintainer
Metadata
1 maintainer
Release files for llama-index-postprocessor-dashscope-rerank 0.6.0
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